CN105653424B - Flight inquiring system reliability estimation method and device - Google Patents
Flight inquiring system reliability estimation method and device Download PDFInfo
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- CN105653424B CN105653424B CN201510999473.1A CN201510999473A CN105653424B CN 105653424 B CN105653424 B CN 105653424B CN 201510999473 A CN201510999473 A CN 201510999473A CN 105653424 B CN105653424 B CN 105653424B
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
- G06F11/3072—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting
- G06F11/3082—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting the data filtering being achieved by aggregating or compressing the monitored data
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3466—Performance evaluation by tracing or monitoring
- G06F11/3476—Data logging
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
- G06F16/3341—Query execution using boolean model
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Abstract
The invention discloses a kind of flight inquiring system reliability estimation method, the method includes：Non-structured raw alarm data is formed into alarm sequence according to time of fire alarming；An alarm subsequence is taken in the alarm sequence, forms time window；Sliding step is set, the entire alarm sequence is traversed on the time window based on the sliding step；The alert data of each time window of cleaning, retains alarm key message, generates alarm database；The alert data in the alarm database in each time window is compressed to form fault data；The fault data is adapted for the adaptable data of reliability model, the data application that the reliability model is adapted is in the representative model of corresponding reliability model, to carry out reliability assessment to flight inquiring system.Correspondingly, the invention also discloses a kind of flight inquiring Reliability evaluation device, realizes passenger and use Self-service cabinet on-line payment, really solve the problems, such as airport network connection outer net.
Description
Technical field
The present invention relates to technical field of aerospace more particularly to a kind of flight inquiring system reliability estimation methods and device.
Background technology
Commercial air flights inquiry system (OpenAv, the Open Availability system) is towards passenger facilities
Flight Information manages system, and which carry a large amount of important services of civil aviaton, to facilitate common user query Flight Information, predetermined machine
Ticket, the personal ticket booking of management facilitate administrator quickly to issue Flight Information, change and manage the predetermined of air ticket.Flight inquiring system
System needs to keep 7*24 hours continuous services, and paralysis even service disruption, the loss of process of some application of system etc. is all
It may result in the paralysis of entire Commercial Air Service.Therefore, the reliability operation of country and civil aviation authority to commercial air flights inquiry system
Propose very high requirement.Currently, using whole process system monitoring mechanism, the daily operation troubles information of operation system all can be by
It is recorded in journal file, certain data support is provided for the reliability assessment of flight inquiring system.
But test number of the data of flight inquiring Reliability evaluation when being not regular software reliability assessment
According to, but system maturation reach the standard grade after by monitoring system TAM from the flight inquiring system operation grabbed from the background when the failure that generates
Information, and be written in real time in the monitoring daily record named with event and form monitoring data, i.e. alarm database.TAM ties up to remind
Shield personnel repair failure in time, and system is just ceaselessly reported an error with the millimetre-sized time once breaking down.Thus exist
When mistake occurs one time, TAM, which may be provided, repeatedly to report an error.So there are two types of the similar mistakes continuously quoted in alarm database
It may：When failure occurs primary and he TAM has been reported repeatedly, when n times have occurred in failure and TAM has reported n times just.So from prison
The set out reliability of assessment flight inquiring system of control daily record needs to properly process physical fault number i.e. Mishap Database and is reported with TAM
Relationship between alert database, but still lack the higher commercial air flights inquiry system reliability estimation method of accuracy at present.
Invention content
To solve existing technical problem, the embodiment of the present invention provides a kind of flight inquiring Reliability evaluation side
Method and device.
In order to achieve the above objectives, the technical solution of the embodiment of the present invention is realized in：
A kind of flight inquiring system reliability estimation method, the method includes：
Non-structured raw alarm data is formed into alarm sequence according to time of fire alarming；
An alarm subsequence is taken in the alarm sequence, forms time window；
Sliding step is set, the entire alarm sequence is traversed on the time window based on the sliding step；
The alert data of each time window of cleaning, retains alarm key message, generates alarm database；
The alert data in the alarm database in each time window is compressed to form fault data；
The fault data is adapted for the adaptable data of reliability model, the number that the reliability model is adapted
According to the representative model applied to corresponding reliability model, to carry out reliability assessment to flight inquiring system.
Wherein, the formation alarm sequence, including：
Non-structured raw alarm data sort out according to fault type and is identified with letter, is sent out further according to failure
The raw time forms alarm sequence.
Wherein, the alarm sequence, which includes multiple between sequence initial time and sequence ends time of time of fire alarming, has
The alarm vector of sequence, the alarm vector includes type of alarm and time of fire alarming.
Wherein, the formation time window, including：According to the alarm sequence feature of commercial air flights inquiry system, using thing
Business quantity determines the size of the time window.
Wherein, the sliding step is not more than the half of the time window.
Wherein, the data of each time window are cleaned, including：The record for lacking alarm key message is deleted, is made every
Alert data in a time window is all valid data.
Wherein, the alert data includes type of alarm, alarms the time occurred.
Wherein, the alert data in the alarm database in each time window is compressed to form fault data, is：It adopts
The alert data in the alarm database in time window is compressed to form fault data with Boolean Model.
Wherein, the fault data of primary fault includes the number of fault type, the time that failure occurs and generation.
Wherein, it is generated in the same time window when same failure twice or when identical alarm more than twice is only remembered
Record is primary fault, and different time of fire alarming is recorded in corresponding fault data.
Wherein, when Same Alarm is only recorded as primary fault when the same time reporting multiple, in corresponding fault data
Only record a time of fire alarming.
Wherein, the reliability model is divided into：Failure time interval model and failure count model；By the fault data
The adaptable data of reliability model are adapted for, including：Time labelling method is simplified using number and indicates event in the fault data
At the time of barrier occurs and stipulated time section；The run time between adjacent failure twice, which is calculated, according to the fault data obtains event
Downtime interval data；The number of faults in stipulated time section, which is counted, according to the fault data obtains failure count data；Institute
It states failure time interval data and indicates that run time between adjacent failure twice, the failure count data were indicated in the stipulated time
The number inside to break down.
Wherein, stipulated time section use work in three shifts time interval partitioning determination.
A kind of flight inquiring Reliability evaluation device, described device include：
Alarm sequence processing module, for non-structured raw alarm data to be formed alarm sequence according to time of fire alarming
Row；An alarm subsequence is taken in the alarm sequence, forms time window；Sliding step is set, the sliding step is based on
The entire alarm sequence is traversed on the time window；
Data processing module, the alert data for cleaning each time window retain alarm key message, generate
Alarm database；The alert data in the alarm database in each time window is compressed to form fault data；
Reliability assessment module will be described for the fault data to be adapted for the adaptable data of reliability model
The adaptable data application of reliability model is reliable to be carried out to flight inquiring system in the representative model of corresponding reliability model
Property assessment.
Wherein, the alarm sequence processing module, is used to form alarm sequence, including：It will be non-structural according to fault type
The raw alarm data of change sort out and is identified with letter, and the time occurred further according to failure forms alarm sequence.
Wherein, the alarm sequence, which includes multiple between sequence initial time and sequence ends time of time of fire alarming, has
The alarm vector of sequence, the alarm vector includes type of alarm and time of fire alarming.
Wherein, the alarm sequence processing module, is used to form time window, including：According to commercial air flights inquiry system
Alarm sequence feature, the size of the time window is determined using transactions.
Wherein, the sliding step is not more than the half of the time window.
Wherein, the data processing module, the data for cleaning each time window, including：Deletion lacks report
The record of alert key message, it is valid data to make the alert data in each time window.
Wherein, the alert data includes type of alarm, alarms the time occurred.
Wherein, the data processing module, for compressing the alarm number in the alarm database in each time window
Fault data is formed according to this, is：Boolean Model is used to compress alert data in the alarm database in time window with shape
At fault data.
Wherein, the fault data of primary fault includes the number of fault type, the time that failure occurs and generation.
Wherein, the data processing module, is used for：Same failure generates twice or two in the same time window
It is only recorded as primary fault when the secondary above identical alarm, different time of fire alarming is recorded in corresponding fault data.
Wherein, the data processing module, is used for：When Same Alarm is only recorded as once when the same time reporting multiple
Failure only records a time of fire alarming in corresponding fault data.
Wherein, the reliability model is divided into：Failure time interval model and failure count model；The reliability assessment
Module, for the fault data to be adapted for the adaptable data of reliability model, including：Time label is simplified using number
Method indicates at the time of failure occurs in the fault data and stipulated time section；It is adjacent twice according to fault data calculating
Run time between failure obtains failure time interval data；The failure in stipulated time section is counted according to the fault data
Number obtains failure count data；The failure time interval data indicate the run time between adjacent failure twice, the failure
Enumeration data indicates the number to break down at the appointed time.
Wherein, the reliability assessment module, is used for：Stipulated time section use is worked in three shifts time interval partitioning
It determines.
The Self-service cabinet method of payment and system of the embodiment of the present invention provide a kind of payer of more convenient and quicker on airport
Formula realizes passenger and uses Self-service cabinet on-line payment, really solves the problems, such as airport network connection outer net, provide simultaneously
It is unified, easily pay the page, compatible a variety of means of payment make payment become more friendly, convenient, fast, and passenger can be with
In the self-service completion payment of Self-service cabinet, facilitates passenger to buy service or the product of airline, greatly promote airport network
Service efficiency facilitates the trip of passenger.
Description of the drawings
In attached drawing (it is not necessarily drawn to scale), similar reference numeral phase described in different views
As component.Similar reference numerals with different letter suffix can indicate the different examples of similar component.Attached drawing with example and
Unrestricted mode generally shows each embodiment discussed herein.
Fig. 1 is the flow diagram of present invention method；
Fig. 2 is alarm sequence example schematic of the embodiment of the present invention；
Fig. 3 is failure time interval data time notation schematic diagram of the embodiment of the present invention；
Fig. 4 is failure count data time notation schematic diagram of the embodiment of the present invention；
Fig. 5 is the composed structure schematic diagram of device of the embodiment of the present invention.
Specific implementation mode
With reference to the accompanying drawings and examples to the commercial air flights inquiry system provided by the invention based on time window sliding
Reliability estimation method is described in detail.
As shown in Figure 1, the commercial air flights inquiry system reliability provided in an embodiment of the present invention based on time window sliding
Appraisal procedure includes the following steps carried out in order：
Step 101：Non-structured raw alarm data is formed into alarm sequence according to time of fire alarming；
Here, non-structured raw alarm data sort out according to fault type and be identified with letter, further according to
The time that failure occurs forms alarm sequence.
Wherein, the alarm sequence, which includes multiple between sequence initial time and sequence ends time of time of fire alarming, has
The alarm vector of sequence, the alarm vector includes type of alarm and time of fire alarming.In practical application, alarm sequence S is by alarming
Multiple orderly alarm vector compositions on type set E, are expressed as S=(s, Ts, Te), Ts is sequence initial time, and Te is
Sequence ends time, s indicate the period that alarm sequence occurs, and are the difference of Te and Ts.For example, the example of an alarm sequence
As shown in Figure 2.As shown in Fig. 2, Ts=0, Te=350, alarm sequence forms (wherein A by multiple orderly alarms vectorial (A, t)
For the type of alarm of certain network element；T is the time that alarm occurs, A ∈ E), it is expressed as<(A,13),(A,36),(B,36),(B,
119),(C,142),(A,168),(A,168),(E,293),(F,312)>。
Step 102：An alarm subsequence is taken in the alarm sequence, forms time window；
Here, it when forming time window, according to the alarm sequence feature of commercial air flights inquiry system, is determined using transactions
The size of the fixed time window.
In practical application, one on alarm sequence S=(s, Ts, Te) alarm subsequence can be expressed as W=(w, ts,
te),ts<t<Te, wherein w=te-ts are known as time window.
Step 103：A fixed sliding step is set, entire alarm sequence is traversed on the time window of above-mentioned determination
Row；
Wherein, the sliding step is not more than the half of the time window.As the alarm sequence of OpenAv is
2013-07-17 to 2013-7-30 totally 14 days data, are to have recorded its fault message with Millisecond.It is determined according to transactions
It fixes time window size, it is 30 minutes to take time window, and sliding step is 15 minutes, traverses entire alarm sequence.
Step 104：The alert data of each time window of cleaning, retains alarm key message, generates alert data
Library；
Here, the record for lacking alarm key message is deleted, it is to have to make the alert data in each time window
Imitate data.Specifically, the data for cleaning each time window, delete some lack alarm key message (alarm network element, type,
Time of fire alarming, rank etc.) record, ultimately generate alarm database, had recorded in alarm database in each time window therefore
Type, time of failure and the failure frequency of barrier.
Here, the alert data in alarm database may include the information such as time that type of alarm, alarm occur.
Step 105：The alert data in the alarm database in each time window is compressed to form fault data；
Since alert event has certain sequential relationship in OpenAv, Same Alarm is not in a time window
Can only it occur repeatedly, and Same Alarm reports repeatedly in the same time sometimes.In order to solve these problems, it is necessary to compress
Alert data generates fault data, to improve the accuracy of reliability assessment.The embodiment of the present invention uses Boolean Model, when same
One failure is only recorded as primary fault when generating multiple identical alarm in window at the same time, but records alarm simultaneously
Different time, with solve alarm sequence problem.
Here, the fault data of primary fault includes the number of fault type, the time that failure occurs and generation.
When same failure generates twice or when identical alarm more than twice is only recorded as primary fault in the same time window,
Different time of fire alarming is recorded in corresponding fault data.When Same Alarm is only recorded as once when the same time reporting multiple
Failure only records a time of fire alarming in corresponding fault data.
Such as：If the A (13) and A (36) that alarms in Fig. 2 is happened in window at the same time, the A that alarms is recorded as once
Failure, the time that failure occurs are denoted as 13s and 36s, and fault data is expressed as A (13,36):1.
Such as：If the A (168) and A (168) that alarms in Fig. 2 is happened at the same time, report repeatedly, then the A that alarms is recorded as one
Secondary failure, the time that failure occurs are 168s, and fault data is expressed as A (168):1.
Step 106：The fault data is adapted for the adaptable data of reliability model；
In order to facilitate the reliability assessment of system, need the fault data of generation being adapted for what reliability model was adapted
Data.Software reliability model can be divided into two classes by the property of software fault process based on software fault history：When failure
Between gap model and failure count model.The fault data that this two class model uses is failure time interval data and failure respectively
Enumeration data.Wherein failure time interval data refer to the run time between adjacent failure twice.Failure count data refer to
The number to break down in stipulated time.
Specifically, step 106 the specific implementation process is as follows：
Fault data is adapted for failure time interval data by step 6.1；
Failure time interval data refer to the run time between adjacent failure twice.In order to provide between adjacent failure twice
Run time, it is thus necessary to determine that at the time of each failure occurs.And it is expressed as day at the time of failure occurs every time in fault data
It goes through and clocks, such as 2013-07-17 22:12:56.In order to facilitate calculating, time notation as shown in Figure 3 is provided.By fault data
It is denoted as the moment 1 when the 0 of first day occurring for failure in library to 1, i.e., by 2013-7-17 00:00:00-00:59:59 are denoted as the moment
1, then by 2013-7-17 23:00:00-23:59:59 are denoted as the moment 24, and so on, by 2013-7-30 23:00:00-23:
59:59 are denoted as moment 24*14=336.The run time that fault data can be so adapted between adjacent failure twice, i.e.,
Failure time interval data required for failure time interval model.
Fault data is adapted for failure count data by step 6.2；
Failure count data indicate the number to break down at the appointed time.First have to determine one it is suitable " when regulation
Between ".Since OpenAv is daily 8:00:00-16:00:00 visit capacity is very big, peaks the phase.Its operation characteristic and " class Three
" work schedule system matches, then will be taken as " for every eight hours " " stipulated time ".The division of specific time interval is daily
0:00:00-8:00:00,8:00:00-16:00:00,16:00:00-24:00:00, and critical count in a upper time interval
It is interior.
Secondly, the time in Mishap Database is provided into a convenient notation.Since failure is every in Mishap Database
It is expressed as calendar at the time of secondary generation to clock, such as 2013-07-17 22:12:56.In order to facilitate calculating, provide as shown in Figure 4
Failure count data time notation.Remember 2013-7-17 0:00:00-8:00:00 is 1,2013-7-17 8:00:00-16:00:
00 is 2,2013-7-17 16:00:00-24:00:00 is denoted as 3, and so on, remember 2013-7-30 0:00:00-8:00:00 is
40,2013-7-30 8:00:00-16:00:00 is 41,2013-7-30 16:00:00-24:00:00 is denoted as 42.
Finally, the failure number occurred at the appointed time is counted, failure count data are formed.It so can be by failure
Data adaptation is the required failure count data of failure count model.
Step 107：The data application that the reliability model is adapted in the representative model of corresponding reliability model, with
Reliability assessment is carried out to flight inquiring system.
Wherein, Reliability Evaluation Model is selected according to the format of above-mentioned failure time interval data and failure count data,
To carry out reliability assessment；In practical application, time window sliding method gives failure time interval data and failure count
Two class reliability data of data selects J-M models and G-O models to be carried out for representative model reliable according to the format of these data
Property assessment.
Specifically, step 107 the specific implementation process is as follows：
Step 7.1 J-M models
Failure time interval model hypothesis time between failures obeys a certain distribution, and the parameter of distribution depends on each time
Number of remaining software errors in interval.Jelinski-Moranda (J-M) model is that the classical of failure time interval model represents
Model, mature, be widely used, Evaluated effect it is good.The basic thought of J-M models is the initial error number in software
One unknown and fixed constant N, each mistake is relatively independent, and mistake is once found and excluded completely immediately, often
As soon as secondary excludes a mistake and do not introduce new mistake during misarrangement, i.e., N subtracts 1 after each misarrangement, whenever soft
Part failure rate is proportional to the residual error number in software, and direct proportion constant is indicated with Φ.
If j is the number of stoppages, Φ (N) indicates software failure rate when remaining N number of mistake, then after first mistake is excluded
Failure rate becomes Φ (N-1), t from Φ (N)1,t2,…,tnIndicate the sample of the time interval between n occurred in succession mistake,
N is all number of errors for up to the present being excluded, in -1 failure of jth of software with the time interval of jth time failure,
Failure rate function is：
λj=Φ [N- (j-1)]
J=1,2 in above formula ..., N.Corresponding Reliability Function is exponential function, i.e.,：
R(tj)=exp [- λ (tj)tj]=exp [- Φ (N-j+1) tj] (1)
With maximum likelihood estimate, the number of errors N and direct proportion constant Φ of Current software can be found out from following formula：
Step 7.2 G-O models
It is located at time series t0＜ t1＜ ... ＜ tnAbove corresponding software cumulative failure number is：y0＜ y1＜ ... ＜ yn, wherein
t0=0, y0=0, a, b are found out by following formula using Maximum Likelihood Estimation Method：
As shown in figure 5, flight inquiring Reliability evaluation device provided in an embodiment of the present invention, including：
Alarm sequence processing module 51, for non-structured raw alarm data to be formed alarm sequence according to time of fire alarming
Row；An alarm subsequence is taken in the alarm sequence, forms time window；Sliding step is set, the sliding step is based on
The entire alarm sequence is traversed on the time window；
Data processing module 52, the alert data for cleaning each time window retain alarm key message, raw
At alarm database；The alert data in the alarm database in each time window is compressed to form fault data；
Reliability assessment module 53, for the fault data to be adapted for the adaptable data of reliability model, by institute
The adaptable data application of reliability model is stated in the representative model of corresponding reliability model, with can to the progress of flight inquiring system
By property assessment.
Wherein, the alarm sequence processing module 51, is used to form alarm sequence, including：According to fault type by non-knot
The raw alarm data of structure sort out and is identified with letter, and the time occurred further according to failure forms alarm sequence.It is described
Alarm sequence includes multiple orderly alarm vectors of the time of fire alarming between sequence initial time and sequence ends time, described
Alarm vector includes type of alarm and time of fire alarming.The alarm sequence processing module 51, is used to form time window, including：
According to the alarm sequence feature of commercial air flights inquiry system, the size of the time window is determined using transactions.Here, institute
State the half that sliding step is not more than the time window.
Wherein, the data processing module 52, the data for cleaning each time window, including：Deletion lacks
The record of alarm key message, it is valid data to make the alert data in each time window.Wherein, the alarm number
According to the time occurred including type of alarm, alarm.The data processing module 52, it is each in the alarm database for compressing
Alert data in time window is to form fault data：Time window in the alarm database is compressed using Boolean Model
Alert data in mouthful is to form fault data.Here, the fault data of primary fault includes fault type, failure generation
Time and generation number.Same failure generates twice or identical alarm more than twice in the same time window
When be only recorded as primary fault, different time of fire alarming is recorded in corresponding fault data.When Same Alarm is on the same time
It is only recorded as primary fault when reporting multiple, a time of fire alarming is only recorded in corresponding fault data.
Wherein, the reliability model is divided into：Failure time interval model and failure count model；The reliability assessment
Module 53, for the fault data to be adapted for the adaptable data of reliability model, including：Time mark is simplified using number
Notation indicates at the time of failure occurs in the fault data and stipulated time section；Adjacent two are calculated according to the fault data
Run time between secondary failure obtains failure time interval data；The event in stipulated time section is counted according to the fault data
Barrier number obtains failure count data；The failure time interval data indicate the run time between adjacent failure twice, the event
Barrier enumeration data indicates the number to break down at the appointed time.Here, the reliability assessment module, is used for：The rule
Section use of fixing time work in three shifts time interval partitioning determination.Specific implementation process has been described in detail in method part above,
It repeats no more.
The embodiment of the present invention to be the problems such as repeatability, false-alarm existing for initial data in Research of reliability model
Starting point provides a kind of flight inquiring system reliability estimation method and device based on time slide window, by original number
According to the alert data for being converted into structuring by time of fire alarming, sets rational time window and sliding step converts alert data
For fault data.In conjunction with the two major classes model of reliability mainstream --- needed for failure time interval model and failure count model
Fault data matching is adaptable therewith failure time interval reliability data and failure count reliability number by data characteristics
According to, and by this two classes reliability data be applied to corresponding representative model J-M, G-O model, with to flight inquiring system progress can
By property assessment.The reasonability and feasibility of time slide window data processing method can be improved flight inquiring system reliability and comment
The accuracy for estimating fault data, to improve the accuracy of flight inquiring Reliability evaluation.
It should be understood by those skilled in the art that, the embodiment of the present invention can be provided as method, system or computer program
Product.Therefore, the shape of hardware embodiment, software implementation or embodiment combining software and hardware aspects can be used in the present invention
Formula.Moreover, the present invention can be used can use storage in the computer that one or more wherein includes computer usable program code
The form for the computer program product implemented on medium (including but not limited to magnetic disk storage and optical memory etc.).
The present invention be with reference to according to the method for the embodiment of the present invention, the flow of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that can be realized by computer program instructions every first-class in flowchart and/or the block diagram
The combination of flow and/or box in journey and/or box and flowchart and/or the block diagram.These computer programs can be provided
Instruct the processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine so that the instruction executed by computer or the processor of other programmable data processing devices is generated for real
The device for the function of being specified in present one flow of flow chart or one box of multiple flows and/or block diagram or multiple boxes.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that instruction generation stored in the computer readable memory includes referring to
Enable the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device so that count
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, in computer or
The instruction executed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
The foregoing is only a preferred embodiment of the present invention, is not intended to limit the scope of the present invention.
Claims (18)
1. a kind of flight inquiring system reliability estimation method, which is characterized in that the method includes：
Non-structured raw alarm data is formed into alarm sequence according to time of fire alarming；
An alarm subsequence is taken in the alarm sequence, forms time window；
Sliding step is set, the entire alarm sequence is traversed on the time window based on the sliding step；
The alert data of each time window of cleaning, retains alarm key message, generates alarm database；
Use Boolean Model to compress the alert data in the alarm database in time window to form fault data, it is primary therefore
The fault data of barrier includes the number of fault type, the time that failure occurs and generation；Wherein, when same failure is same
It is generated in one time window twice or when identical alarm more than twice is only recorded as primary fault, corresponding fault data
It is middle to record different time of fire alarming；When Same Alarm is only recorded as primary fault when the same time reporting multiple, it is corresponding therefore
Hinder and only records a time of fire alarming in data；
The fault data is adapted for the adaptable data of reliability model, the data that the reliability model is adapted are answered
For the representative model of corresponding reliability model, to carry out reliability assessment to flight inquiring system.
2. according to the method described in claim 1, it is characterized in that, the formation alarm sequence, including：
Non-structured raw alarm data sort out according to fault type and is identified with letter, is occurred further according to failure
Time forms alarm sequence.
3. method according to claim 1 or 2, which is characterized in that the alarm sequence includes that time of fire alarming rises in sequence
The multiple orderly alarm vectors to begin between time and sequence ends time, when the alarm vector includes type of alarm and alarm
Between.
4. according to the method described in claim 1, it is characterized in that, the formation time window, including：
According to the alarm sequence feature of commercial air flights inquiry system, the size of the time window is determined using transactions.
5. method according to claim 1 or 4, it is characterised in that：The sliding step is no more than the time window
Half.
6. according to the method described in claim 1, it is characterized in that, the data of each time window of cleaning, including：It deletes
Lack the record of alarm key message, it is valid data to make the alert data in each time window.
7. according to the method described in claim 6, it is characterized in that, the alert data includes type of alarm, alarm generation
Time.
8. according to the method described in claim 1, it is characterized in that,
The reliability model is divided into：Failure time interval model and failure count model；
The fault data is adapted for the adaptable data of reliability model, including：Time labelling method table is simplified using number
Show in the fault data at the time of failure occurs and stipulated time section；Adjacent failure twice is calculated according to the fault data
Between run time obtain failure time interval data；The number of faults in stipulated time section is counted according to the fault data to obtain
To failure count data；The failure time interval data indicate the run time between adjacent failure twice, the failure count
Data indicate the number to break down at the appointed time.
9. according to the method described in claim 8, time interval is drawn it is characterized in that, stipulated time section use is worked in three shifts
Point-score determines.
10. a kind of flight inquiring Reliability evaluation device, which is characterized in that described device includes：
Alarm sequence processing module, for non-structured raw alarm data to be formed alarm sequence according to time of fire alarming；
An alarm subsequence is taken in the alarm sequence, forms time window；Sliding step is set, based on the sliding step described
The entire alarm sequence is traversed on time window；
Data processing module, the alert data for cleaning each time window retain alarm key message, generate alarm
Database；Boolean Model is used to compress the alert data in the alarm database in time window to form fault data, one
The fault data of secondary failure includes the number of fault type, the time that failure occurs and generation；Wherein, when same failure
It is generated in the same time window twice or when identical alarm more than twice is only recorded as primary fault, corresponding failure
Different time of fire alarming is recorded in data；When Same Alarm is only recorded as primary fault when the same time reporting multiple, accordingly
Fault data in only record a time of fire alarming；
Reliability assessment module will be described reliable for the fault data to be adapted for the adaptable data of reliability model
Property the adaptable data application of model in the representative model of corresponding reliability model, commented with carrying out reliability to flight inquiring system
Estimate.
11. device according to claim 10, which is characterized in that the alarm sequence processing module is used to form alarm
Sequence, including：Non-structured raw alarm data sort out according to fault type and is identified with letter, further according to failure
The time of generation forms alarm sequence.
12. the device according to claim 10 or 11, which is characterized in that the alarm sequence includes time of fire alarming in sequence
Multiple orderly alarm vectors between initial time and sequence ends time, the alarm vector includes type of alarm and alarm
Time.
13. device according to claim 10, which is characterized in that the alarm sequence processing module is used to form the time
Window, including：
According to the alarm sequence feature of commercial air flights inquiry system, the size of the time window is determined using transactions.
14. the device according to claim 10 or 13, it is characterised in that：The sliding step is not more than the time window
Half.
15. device according to claim 10, which is characterized in that the data processing module, it is each described for cleaning
The data of time window, including：The record for lacking alarm key message is deleted, the alert data in each time window is made
All it is valid data.
16. device according to claim 15, which is characterized in that the alert data includes type of alarm, alarm generation
Time.
17. device according to claim 10, which is characterized in that
The reliability model is divided into：Failure time interval model and failure count model；
The reliability assessment module, for the fault data to be adapted for the adaptable data of reliability model, including：It adopts
Simplify at the time of time labelling method indicates that failure occurs in the fault data and stipulated time section with number；According to the event
The run time that barrier data calculate between adjacent failure twice obtains failure time interval data；It is counted and is advised according to the fault data
The number of faults in section of fixing time obtains failure count data；The failure time interval data indicate between adjacent failure twice
Run time, the failure count data indicate the number to break down at the appointed time.
18. device according to claim 17, which is characterized in that the reliability assessment module is used for：When the regulation
Between section use work in three shifts time interval partitioning determination.
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| CN115865611B (en) * | 2021-09-24 | 2025-02-28 | 中国移动通信集团湖南有限公司 | A method and device for handling network equipment failure, and electronic equipment |
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